\section{Findings}
\label{sec:findings}

Previously we mentioned that in this section we condense meanings from the tho\-ughts, statements, and opinions of the primary data. We juxtapose this meaning condensation with what \cite{JONES} refer to as selective coding where core categories are catalysed and become apparent. The section is structured on the basis of the coding. Throughout the section we will elaborate on the data by means of our current knowledge, i.e our secondary data, and our research question. \bigskip

\noindent The following three topics are the results of this coding:

\begin{itemize}

\item Business silos breakdown -- the necessity for a holistic approach.
\item Top-down versus bottom-up approaches.
\item Maturity -- the importance of a collective open data mindset.

\end{itemize}


\subsection{Business silos breakdown -- the necessity for a holistic approach}
\label{subsec:silosbreakdown}

In the literature review, primarily section \ref{sec:maturity}, we referred to existing maturity models depicting various kinds and scopes of maturity. Most of them emphasized the importance of a holistic mindset when tackling cross-department/unit problems. \bigskip

\noindent \cite{ROSSWEILL}, figure \ref{fig:rossweillmaturity}, address maturity from an Enterprise Architecture perspective and identify the ability to be agile, flexible, and responsive to shifting requirements as the optimum. An organisation has to reach the optimised stage by following an evolutionary path where their business silo mindset is stepwise broken down and the organisation incrementally evolves its collective maturity to take cross-silo decisions, which have to be supported by a cross-silo IT architecture.

IDC Government Insights' smart city maturity model \citep{IDC} is very similar to the above mentioned model even though it is addressed to cities instead of companies. One can see this as an attempt to treat the city as an organisation to comprehend the inherent complexities. They too have identified a final stage which has sustainable characteristics -- the city is agile and understands how to continuously improve and align the areas of strategy, IT, and governance in a de-siloed manner. Cross-department thinking, mindset, and willingness is crucial for the smart city to sustain in following the pace of development in the long run. The de-siloed city is willing to take the risks of holistic, long-term thinking because they carry greater weight than the risks of not doing so.

The Open Government maturity model by Gartner (figure \ref{fig:gartner}) depicts how a city can benefit from being open and strive for collaboration and engagement in maturity levels 4 and 5. They present Open Government as an inevitable asset to successful and sustainable smart city initiatives where overall strategies are enterprisewide and engaging all relevant actors. This is similar to fostering a collective mindset across the city, across the various actors. The underlying point is that a holistic approach is needed to establish a sustainable smart city ecosystem. The public sector also has to break down their business silos and look for cross-department synergies for the projects to become a reality and sustainable. \bigskip

\noindent All in all it seems like an overall vision is to minimize the risks of a deep lock-in to these business silos, which prevents the city to harvest the value of horizontal integrations within the cities. But there are still many unanswered questions for us to be able to make a conceptual model for institutional design that contributes to a business silo breakdown. Who are the relevant actors, besides the overall public sector, that have to break down their silos? How can you do such a breakdown from a city perspective and is it altogether possible? How to make these actors willing to participate in such a process? We will now search for answers to these questions in our primary data, the interviews in Appendix \ref{app:transcriptions}.\bigskip

\subsubsection{The nature of silo-thinking in a smart city context}

\noindent Adrian Ulisse is describing how the unwillingness to share information is an obstacle to the required collaboration for aligning mindsets:

\begin{quote}
\textit{``I did my first project in smart cities, at the time called intelligent cities. It was a project out in Malaysia where they were building a new city for a half million people. That was very interesting because I learned that it wasn't a technology issue, it was actually a more people and organizational issue. We visited every single government department in the city and found that lots of the individuals wanted to share or conceive data but were less comfortable about sharing their own data, which was an interesting observation.''} (Appendix \ref{appsec:adrian}, 02.55)
\end{quote}

\noindent The necessity for institutional redesign was identified before the introduction of smart cities. We can address this as an institutional issue because the interactions between parties are \textit{not} contributing to the functioning of a technological system. There are no established rules of the game that ensure a win-win situation yet.

Ville Meloni adds to that and describes how the future business environment requires new ways to collaborate to become agile and respond to external challenges. This requires an insight to other business domains and therefore an understanding of the necessity for opening up your own domain:

\begin{quote}
\textit{``the logic is that in a closed system, whether it's closed data or closed source which is not sharing information, the idea is that it's very inefficient. In the future there are a lot of challenges, there is less money, things change more quickly, there is digitalisation. So, you need to be more agile and we believe that one of the ways for that to happen is to open up your processes, open up your data and collaborate and work together. And that enables hopefully cost savings, better services and that also hopefully enables reacting quicker both citizen and company needs instead of being very closed and not cooperating.''} (Appendix \ref{appsec:villemeloni}, 32.02)
\end{quote}

\noindent It is not sufficient to enclose oneself in a comfortable silo with no apparent uncertainties. Open data can contribute to give birth to this new collaboration. 

Søren Møller Jensen outlines the triple-helix ecosystem that has to be institutionalised for open data solutions to become successful:

\begin{quote}
\textit{``First of all [we have] the public authorities. They own some of those resources, they control how the resources are handled and how the infrastructures build up. And you of course have the companies who are the ones most well suited to come up with commercially feasible solutions and the most cost effective solutions. And finally the knowledge institutions of course they [are] a very important independent partner. They can be the ones trying to create a link between public authorities and companies because very often we hear companies complaining that the municipalities don't get the ideas of what the companies technologies are able to do.''} (Appendix \ref{appsec:sorenmollerjensen}, 25.39)
\end{quote}

\noindent And so, these three triple-helix actors have to have an in-depth understanding of each others domain and do cross-sectoral thinking. Adrian Ulisse is depicting that the main governance structure is not capable of thinking holistically because of its embedded opposing institutional design. And so, it requires some incentives and eye-openers for the public sector to look outside their own subsystem:

\begin{quote}
\textit{``The very nature of the central governments is broken into silos -- from ministry of transport to ministry of energy etc.''} (Appendix \ref{appsec:adrian}, 17:00)
\end{quote}

\noindent It is a matter of facilitating a collaboration between these city actors which requires them to understand and treasure mutual benefits and synergies. There is a false security in sticking to the secure and familiar environment of ones own business silo. Kristoffer Hvidsteen gives an example of this:

\begin{quote}
\textit{``If you don't think about aspects beyond the single bottom-line you are at great risk, and in some industries really great risk, of overlooking important aspects of your role as a company, your role as an organization, which will limit your ability to create value for your clients, especially in the medium and longer term matters, to be able to function properly and effectively. So in that sense it's an emerging scope for many companies and organizations to start thinking about this in a holistic and a systematic manner.''} (Appendix \ref{appsec:hvidsteen}, 04:35)
\end{quote}

\noindent So you have to think holistically to ensure a long-term sustainability of any company or organisation. Henrik Korsgaard also gives an example:

\begin{quote}
\textit{``The main obstacle is that everybody working in this space is employed or working from a particular perspective. So if you are working in a municipality, you either work with sewage, traffic, or child day care, so you have a very narrow perspective. You see one slice of the holistic pie, so to speak. The same goes for industry. You have a market, where you don't sell holistic solutions. You sell solutions for a specific market, right?''} (Appendix \ref{appsec:henrik}, 13:10)
\end{quote}

\noindent The problem is, according to Henrik Korsgaard, that the normal \textit{siloed} value chain breaks down and becomes much more distributed along a very complex network of stakeholders (Appendix \ref{appsec:henrik}, 16.00), which can catalyse deal breaking uncertainties to the relevant and necessary actors. Søren Kvist is concurrently saying that \textit{``the city is very much focused on what their responsibilities are at their department.''} You have to look between these silos to reap the value of the synergies lying in between them (Appendix \ref{appsec:kvist}, 10.00) but \textit{``today there is really no formal institutions are supposed to make this increased collaboration work between sectors when it comes to smart city.''} (Appendix \ref{appsec:kvist}, 12:20) \bigskip

\noindent New institutions have to be formed for the open data silo breakdown to work, institutions that normalize the act of holistic thinking when doing cross-sector collaboration:

\begin{quote}
\textit{``When these organisations are used to work in silos, it's in their like organizational culture to focus on one thing from their perspective and then this data opens the eyes and [they think]: `OK. Wow. I can look at this from 5 or 10 different perspectives.' I think many understands that it makes sense because if you take this things better into account it's more sustainable. You do less of the same or you keep inventing a wheel. But it also means that you need to collaborate and then take a lot more things in to account. It's very painstaking at first because you need to agree on how to do this.''} (Appendix \ref{appsec:villemeloni}, 23:10)
\end{quote}

\noindent The organisations might accept that somewhere inside their data, potential value is hidden. And that value might only indirectly come back to themselves if they make them open. So new institutional design has to consider how to make this value more tangible. This is a way to realize a sustainable collaboration environment based on open data. \bigskip

\noindent Open data is a means to enable integration across business silos which is vital for harvesting the mentioned synergies. Søren Møller Jensen emphasizes how holistic thinking is the only way to achieve sustainable solutions where the smart city actors can benefit from the data and information of each other:

\begin{quote}
\textit{``Sustainability comes from better integration across the various different silos in different cities. Transportation and energy is very much interlinked but very much run separately in terms of how they operate it. Not one element works optimally in isolation. [...] I think another thing you see happen across the world is trend of sharing business models. When you walk around in a city you start to realize that we are buried in inefficient use of our resources.''} (Appendix \ref{appsec:adrian}, 11:10)
\end{quote}

\noindent Søren Kvist agrees with that and says that \textit{``if we use data in a more targeted way than we have done so far, we can use it to use the resources within the city more efficiently''} (Appendix \ref{appsec:kvist}, 06:45). Ville Meloni has the same point and explains how open data has a two-sided effect. If treated correctly data sharing can catalyse collaboration and engage in a cross-sectoral learning process. At the same time it is a catalyst to opening up more data and utilise it horizontally with the overall goal to exploit common and privately held resources more efficiently:

\begin{quote}
\textit{``I think there are lot of things that you can do with data, lot of understanding, you can optimize things better, you could sort of share more, you could collaborate more and you could sort of, I guess its also a way of learning.''} (Appendix \ref{appsec:villemeloni}, 06:01)
\end{quote}

\noindent This understanding of each other's domain is one of the pillars in smart cities, which enforces a holistic mindset where the actors ideally should be so mature that they understand that sustainable long-term goals can be met by increasing the total value of the smart city system and its subsystems. Henrik Korsgaard elaborates on this:

\begin{quote}
\textit{``Understanding the needs of the other and understanding that what is valuable for me, that is both for private and business levels, is not valuable for you. That is what is changing with the smart city.''} (Appendix \ref{appsec:henrik}, 14:30)
\end{quote}

\noindent But still there is a long way to reach this inherent mutual understanding of each other's domain. The public sector is often the initiator of data-driven smart city initiatives, but they are not sustainable because they need data from other departments or the private sector to really yield some value - cross-sectoral open data mindsets are simply vital for its success. Adrian Ulisse explains this situation:

\begin{quote}
\textit{``you have central government officials trying to react to something rather than actually properly plan. One of the big issues, and it's a wider issue than just for smart cities, is there is a level of distrust between the private and public sector. [...] The understanding of what problem you are trying to solve is not being thought through. So as they may publish one data element you can't solve the problem without other elements of data and that might be from the private sector, it might as well be from citizens.''} (Appendix \ref{appsec:adrian}, 23:20)
\end{quote}

\noindent Cross-silo-thinking is an important means to the creation of the smart city as a whole where data has to be allowed to flow across sector boundaries enabling sustainable smart initiatives to emerge. Open data is not a goal in itself but a means to achieve a range of goals within the smart city. 

\begin{quote}
\textit{``[Cross-silo-thinking] is a very important manner as for the ability to see new connections, how your professional sector might relate to the other competencies. Also it's a matter of mindset because you need to pro-actively challenge your own competences and the area you are working within and how that might will be able to relate that to other areas. You cannot just do that just re-actively because very often if you only being re-active you will never see the possible new relation, you are very likely to get stuck within your own area.''} (Appendix \ref{appsec:sorenmollerjensen}, 14:00)
\end{quote}

\noindent Of course it requires some open data maturity for a smart city actor to understand how to make the benefits of challenging its own working area weight higher than the (false) security of concerning itself with its own familiar business silo. He goes on and explains how Copenhagen Connecting is

\begin{quote}
\textit{``trying to focus this mindset. And you can say that the willingness to actively challenge whatever existing solutions you have that could be one of the indicators you have.''} (Appendix \ref{appsec:sorenmollerjensen}, 37:55)
\end{quote}

\noindent What Søren Møller Jensen is saying here goes along with the smart city wheel by Boyd-Cohen (figure \ref{fig:boyd}) who argues that a smart city has to have some indicators to measure the progress of the city. This willingness to pro-actively challenge your existing solutions, working areas, and competencies is linked to the agility of the actor to adopt to external developments and new requirements. An agility that can only be reached if a horizontally integrated mindset is developed so sustainable cross-silo solutions can be fostered. Søren Kvist also elaborates on the necessity of breaking down business silos:

\begin{quote}
\textit{``The challenge is that you need an increased collaboration between different business units if you want to make better solutions. Because otherwise you will just do silo solutions, meaning that you will roll out one solution for specific business units throughout the whole city and that's not necessarily the best way to do it. It's not that it's not going to work technically but it's not necessarily the best technical solution and you wont really harvest the synergies between thinking cross-horizontally.''} (Appendix \ref{appsec:kvist}, 13:30)
\end{quote}

\noindent In the introduction, section \ref{sec:researchsignificance}, we mentioned the Big Data Infrastructure tender managed by the cluster CLEAN formerly known as Copenhagen Cleantech Cluster. Unfortunately we were not able to get an interview with any of the responsible people of this tender inside CLEAN, but it is still interesting for us because it is meant to be a way to actually catalyse the kind of collaboration and mutual understanding that we have addressed so far. Søren Møller Jensen is mentioning it:

\begin{quote}
\textit{``Who ever wins going to have a task of running that infrastructure but whatever happens on top of that they are not supposed to restrain and I don't see how they could restrain that. [...] basically it supposed to be infrastructure, which can subsequently be accessed, by lots of other companies and public authorities and whomever.''} (Appendix \ref{appsec:sorenmollerjensen}, 32:00)
\end{quote}

\noindent As we do not have any primary data or in-depth secondary data about this Big Data Infrastructure we can only assume what its potential purposes are. We do not know the detail levels of the project plans and to which extend the obligations for the winner are formulated. We do not even know anything about its specific substance. But the idea of having a platform run by a keystone actor with obligations set by a knowledge institution is not irrelevant to our research. 

\subsubsection{Obstacles towards business silo breakdown}

\noindent Great uncertainties emerge when silos disintegrate and there is some evident reluctance towards holistic thinking:

\begin{quote}
\textit{``Every time you make a new system and change the existing systems you need to take into account the consequences of this. Just as the value chain is breaking down and becoming more distributed, so is the causal relationships in the city. So, every time you build a new system where you take some data in, you might marginalise and hurt somebody.''} (Appendix \ref{appsec:henrik}, 27:30)
\end{quote}

\noindent For open data to become a part of the smart city, you have to anticipate rebound effects and unintended effects in the long run. One way to do that is to start with a small well-defined subsystem as a solution to a specific city issue. In such a subsystem an ecosystem can be built with understandable value propositions that every actor should benefit from in the end. This will make the open data solution sustainable by designing an institution based on some form of mutual agreement and aligned mindsets. \bigskip

\noindent Lasse S. Vestergaard points at another obstacle for business silo breakdown, which is not compatible with the required agility:

\begin{quote}
\textit{``if we can begin to look at data that we have never looked at before and when we try to merge that we will be able to have new knowledge and even within the municipalities, not only municipalities, within the public sector they are already today aware of that if they could aggregate two specific data sets, they would be able to get completely new insights. But they can't because of legislation.} (Appendix \ref{appsec:lassesteenbockvesteraard}, 18:41)
\end{quote}

\noindent We do not have the expertise to elaborate on the inherent legal issues in the aggregation of data, but it is just to mention that there is a framing legal institution confining the subsystem of matter. This legal institution is more difficult for us to handle. \bigskip

\noindent The quality of the data is also a very big obstacle for using it as a means to enhance collaboration and silo breakdown. Lasse S. Vestergaard says that 

\begin{quote}
\textit{``if the quality of the data is not good enough you cannot create anything but if you don't understand the data it's really hard too because you need to work from both sides: You need to have a better quality of data but you also need to get a better mindset for a better understanding of what you can do with the data.''} (Appendix \ref{appsec:lassesteenbockvesteraard}, 43:00)
\end{quote}

\noindent Two things are required for open data to be beneficial for other smart city initiatives: (1) You have to have data of a certain quality - that might follow the guidelines by \cite{TAUBERER} (figure \ref{fig:tauberer}) so the right data type and exposure mechanism is chosen from the beginning - and (2) you accordingly have to develop a mindset that understands the data and the exposure mechanisms. These two conditions are causal for silo breakdown to happen by means of open data.

These conditions leads to interoperable data and Ville Meloni explains how the ecosystem should use the expert companies to foster the interoperability:

\begin{quote}
\textit{``So, I think the interoperability of the data and the data quality [is important] and I think there is a big role for IT companies and other companies to actually take the data and help the government and other data owners to make it more interoperable.''} (Appendix \ref{appsec:villemeloni}, 18:04)
\end{quote}

\subsubsection{Incentivisation towards business silos breakdown}

We will now go through the statements that point actions that can be taken to break down business silos. Adrian Ulisse is describing how funding is vital as incentive for financial leaders to encourage more integrative thinking and break down business silos:

\begin{quote}
\textit{``I think you have to use the financial leaders to encourage more integrative thinking, and that might be moving funding or making funding dependent on action.''} (Appendix \ref{appsec:adrian}, 19:22)
\end{quote}

\noindent It is important to establish some direct economic incentives for the actors to be willing to participate but incentives can also be more indirectly economic. Søren Møller Jensen explains how the actors can develop an understanding of how to harvest value from getting access to foreign data and share their own data:

\begin{quote}
\textit{``... you need to consider what might incentives be for me to open up the access to that data for another company. Imagine another company, for example within finance or insurance, get access to a wider pool of data. Then they might be able to offer me some sort of service -- not necessarily a physical product, but it could be some sort of other service.''} (Appendix \ref{appsec:sorenmollerjensen}, 08:18)
\end{quote}

\noindent He goes on and says that it is a very difficult task of formulate value creation which is not abstract and not related to the overall system level:

\begin{quote}
\textit{``... it is much easier to describe or formulate how that value can be extracted on the society level. I mean you can also formulate how it can create value in the individual level but the thing is if this is going to happen, you would need some sort of ability or desire to pay at individual level otherwise you would have say if you have all of those solutions be legalized through taxes.''} (Appendix \ref{appsec:sorenmollerjensen}, 06:08)
\end{quote}

\noindent This implies that the initial success of an open data initiative should focus on value proposition that result in short term wins directly for the actors. This will function as an understandable incentive to participate. Henrik Korsgaard explains that even though you have the initial funding for setting up an infrastructure for collecting valuable data on a city level, it does not provide sustainable value if incentives structure for sharing that data are not established:

\begin{quote}
\textit{``You have to give, for instance, a guy in the traffic department a certain budget to fix the street, to set up sensors that can harvest data and so forth. But you wont be able to link what he does to what a business does.''} (Appendix \ref{appsec:henrik}, 17:30)
\end{quote}

\noindent Søren Kvist continues this argumentation and says that 

\begin{quote}
\textit{``if we can reuse the building blocks between different business domains [...] then we can provide better solutions and we can provide new insight in regards to making solutions better.''} (Appendix \ref{appsec:kvist}, 15:16)
\end{quote}

\noindent He gives a more concrete example of a business model expansion using open data in the insurance domain. It requires a special kind of collaboration and mutual understanding to reach a stage where such initiatives can be realized. Yet Copenhagen Solutions Lab has not looked into this:

\begin{quote}
\textit{``of course there is a high incentive for insurance companies to make these solutions a success, because that will mean that the damages caused by cloud bursts will be a lot lower because we will know where there are humidity problems, and one can see the damages in real time and they can do things to try to minimize the causes of the damages. And that's a good business case for the insurance companies. So that's another element of an incentive that could be interesting to further explore. We haven't gone there yet.''} (Appendix \ref{appsec:kvist}, 43:00)
\end{quote}

\noindent It seems inevitable to use some resources for making projects tangible and establishing an understanding of the business domain of a single foreign actor. Incentives are easier to formulate if one can plan for short term wins to achieve long-term goals:

\begin{quote}
\textit{``it seems that there might be more, let's say, immediate success in focusing on a specific department and try to see what they have and may be even a department with good data source like Geo Data''} (Appendix \ref{appsec:lassesteenbockvesteraard}, 38:14)
\end{quote}

\noindent If we relate that to systems theory, Lasse S. Vestergaard suggests that systems should be broken into subsystems until their complexity is quantifiable and manageable. Then value is easier to formulate on an individual level.

If projects have a clear short-term goal then concrete action can be taken and value propositions can be made very visible. Ville Meloni also emphasizes that open data projects initially have to be concrete for an ecosystem to emerge around the data:

\begin{quote}
\textit{``certain entities have to put commitments to do something concrete so that it make sense and also invest time and sort of communications and develop with developers and with people from the ecosystem. Not only from the traditional IT companies but also people who are enthusiastic about it and just try to look at this ecosystem and you try to help different actors to understand and to do something concrete.''} (Appendix \ref{appsec:villemeloni}, 12:40)
\end{quote}

\noindent He further explains that the whole open data paradigm requires actors to understand, contribute to, and benefit from open innovation. Open data is indeed a means to break down silos -- especially if concrete projects are formulated, which can grow bigger gradually as the open innovation grows and actors increasingly understand:

\begin{quote}
\textit{``you should not just open data that you think is good for business but you should open large kind of different types of data because you can never know because it's open innovation. You can't really know how somebody is using that but it helps to create new angles and new sort of innovation based on new ways of mixing different data. So, we have that in mind but definitely quick wins, if you can find quick wins and concrete use cases that you know could be solved, I mean some business problems that could be solved by doing something with the open data then you should look at those.} (Appendix \ref{appsec:villemeloni}, 27:25)
\end{quote}

\noindent Ville Meloni goes on and describes how subsystems identification is a vital way to create incentives for actors to participate. After a while the project can be taken to a larger scale where the actors are able to find other actors and help each other mature:

\begin{quote}
\textit{``Let's say that if I now collaborate and open my data, then I will some how benefit from it concretely. [\ldots] You [have to] start small, take entities like individuals and organizations that really need this and see the benefit and really do invest the time and then you experiment with them and then share best practices before you take anything to large scale.''} (Appendix \ref{appsec:villemeloni}, 24:19)
\end{quote}

\noindent One way to foster open innovation and well-considered open data is to physically place potential actors next to each other and incentivize them to discuss and find synergies. Copenhagen Solutions Lab is doing something very correctly according to Lasse S. Vestergaard:

\begin{quote}
\textit{``that an interesting approach because this way what they do is, they actually try to assemble people from different departments within the municipality so they can sit physically together and hopefully they will talk together and figure out that; well we are doing stuff in parallel, and well, we can actually collaborate in this, and they are doing exactly the same.} (Appendix \ref{appsec:lassesteenbockvesteraard}, 45:59)
\end{quote}

\noindent We have previously mentioned that open data and open innovation is both an enabler to other data-driven smart city initiatives and at the same time it is a goal in itself that can lead to concrete value creation based on its aggregation with other open data. Ville Meloni here describes how understanding of the value of open data can function as an incentive in itself:

\begin{quote}
\textit{``I think open data is a way for different organizations and individuals to collaborate concretely. For example, in analysis or creation of digital services or just sharing and understanding. It's something concrete. It's like a fuel for these things.  And if I think the cities from the public sector perspective, I think, one of the thing it has enabled is this, quite traditional organizations which might work in silos, it helps them to collaborate and it helps them to understand each other and helps them to understand how they function because they look at the data and they get different perspectives from their data''} (Appendix \ref{appsec:villemeloni}, 04:21)
\end{quote}

\subsection{Top-down versus bottom-up approaches}
\label{subsec:topdownvsbottomup}

%The general description of top-down and bottom-up approaches is that top-down approach focuses from top or abstract level, breaking down into systems and then to sub-systems, whereas a bottom-up approach focuses from the lowest level of sub-systems, combining them to form a system and so on.

For a very long time, city development and planning has been dominated by top-down approaches but with the introduction of smart cities and emergence of technologies like Web 2.0, the bottom-up approach has gained lot of attention \citep[p. 46]{SCHAFFERS2012}. Involvement of people in defining and implementing solutions is argued to be the fundamental trend of smart cities \citep[p. 53]{SCHAFFERS2012}. One way involve people is by opening data and making it publicly available (section \ref{subsec:relevanceofopendata}). We have also explained how open data can bring together smart city actors and catalyse smart city development (subsection \ref{subsec:relevanceofopendata}). But there are still some questions unanswered regarding the implementation of open data initiatives/systems. Who are responsible for implementing these systems? who should initiate it? What approach fits the best (top-down or bottom-up)? We will now explore our primary data (interviews in Appendix A) to find answers to these questions. \bigskip

\noindent Adrian Ulisse explains that there is a tendency of putting lot of effort in top-down approach while implementing big systems and this may decrease the possibility to understand the optimal value and impact it has:

\begin{quote}

\textit{``Working for a big systems integrator, there is often a tendency to take a top-down approach and say that you can integrate all of these different systems, put lots of different sensors in the field, and it's all going to be great and wonderful. The question that often is not asked is: Why are you going to do that? What are the benefits? What are the impacts that are going to happen on this earth? Is a big top-down system the right way to go? I haven't had that experience. I thought: let's look at it from a different perspective and in a different way.  With a more bottom-up approach , where you have got a predetermined position - you are just trying to understand what are the problems that we are trying to solve within the city.''} (Appendix \ref{appsec:adrian}, 04:15)

\end{quote} 

\noindent  From above statement, it can be argued that open data initiatives as big and complex systems need to balance top-down approaches and the bottom-up approaches. \cite{EU3} illustrate (figure \ref{fig:approaches} how top-down and bottom-up approaches can encourage the participation of citizens and stakeholders in the smart cities. They argue that a top-down approach provides a high degree of control and coordination among the actors in the smart city, whereas a bottom-up approach allows the participation of the actors in the smart city development process. According to systems theory, one way to approach such a complex system is to break it down into tangible and concrete projects (subsection \ref{subsec:applyingsystemstheory}) that can be developed by balancing top-down and bottom-up approaches. This can be seen as bottom-up system optimisation. Ville Meloni supports this by saying,

\begin{quote}

\textit {``I think, there is a test somebody has to do or certain entities have to put commitments to do something concrete so that it makes sense and also invest time and sort of communication and develop with developers and with people from the ecosystem.''} (Appendix \ref{appsec:villemeloni}, 10:44)

\end{quote}

\noindent This depicts that the development of open data subsystems requires a proper identification of concrete projects within the city. Henrik Korsgaard argues that the initiation of such projects should be top-down and \textit{``it should be the policy-makers that take the initiative to make people and actors understand that they can benefit each other by opening up data''} (Appendix \ref{appsec:henrik}, 19:25). Ville Meloni further supports this statement by indicating that cities are the main responsible actors for taking the initiatives. He explains it by saying,

\begin{quote}

\textit{``In the beginning, Helsinki and other metropolitan cities, they took the step to invest time and money in starting open data operations and concretely opening data. [...] .So, I think its the public sector players who actually invest time and money to open their data.''} (Appendix \ref{appsec:villemeloni}, 13:35) 

\end{quote}

\noindent Adrian Ulisse explains the necessity of top-down approach in breaking the silo thinking of relevant actors and he also depicts it as a role of central government.

\begin{quote}

\textit{``I think central government has a point to play in this. The very nature of the central government is broken into silos - from ministry of transport to ministry of energy e.t.c. If you can incentivize local government by integrating at the central government level.''} (Appendix \ref{appsec:adrian}, 16:15)

\end{quote}

\noindent It can be argued that the initiation of open data initiatives should be done by governance bodies (i.e. top-down approach), or what \cite{IANSITY} define as Keystones, and proper institutions should be designed to incentivise and create a suitable environment for other actors to get involved in the process. Ville Meloni explains his view by saying,

\begin{quote}

\textit{``I think it's public sector players who [should] invest time and money to open their data and I think it's not opening data for [just] opening data. It should be taken [into consideration] that when new IT systems are implemented there are open APIs by default [...] and make sure that it is also mandated and there can even be laws. Lot of this open data development is from grass roots level in the beginning, you have individual level at first and you then you have smaller companies doing something and then you have some well established IT companies who understand that this open data is good for their business.''} (Appendix \ref{appsec:villemeloni}, 13:35)

\end{quote}

\noindent All in all, it is about applying proper top-down approach and creating appealing environment for other actors (private sectors and citizens) to get involved and catalyse a bottom-up approach.  \bigskip 

\noindent In section \ref{subsec:opendatainnovationenabler} we explained that open data is an innovation enabler and we also explained how an open data system can function as a platform for open innovation (section \ref{sec:openinnovationtheory}). Ville Meloni also indicates the benefits of open data and explains how opening of data can make work processes efficient and make the public and private sector more responsive.

\begin{quote}

\textit{``The logic is that in a closed system, whether it's closed data or closed source, which is not sharing information, it is very inefficient. In the future, there are lots of challenges, there is less money, things change more quickly, there is digitalisation. So you need to be more agile and we believe that one of the ways for that to happen is to open up your processes, open up your data and collaborate and work together. And that enables, hopefully, cost savings, better services and that also hopefully enables reacting quicker to whether it is citizens or company needs instead of being very closed and not cooperating.''} (Appendix \ref{appsec:villemeloni}, 32:02) 

\end{quote}

\noindent There are lot of issues in setting up open data systems and one of the major issues is funding. Kristoffer Hvidsteen express the necessity of policy for funding open data:

\begin{quote}

\textit{``A policy initiative, like funding a platform where you propagate the data, I think is a fantastic good initiative to take.''} (Appendix \ref{appsec:hvidsteen}, 26:12)

\end{quote}
 
\noindent It is crucial to identify the \textit{``innovation investors and benefactors''} (\ref{subsec:stepsindevelopinginnovation}). Adrian Ulisse explains the powerful role of investors by saying, 

\begin{quote}

\textit{``I think you have to use the financial leaders to encourage more integrative thinking and that might be by moving funding dependent on action''} (Appendix \ref{appsec:adrian}, 19:08)

\end{quote}

\noindent Kristoffer Hvidsteen explains that the public sector should be able to provide funds in the absence of venture capital funds (Appendix \ref{appsec:hvidsteen}: 41:33) and also indicates a lack of confidence in the public sector as a major barrier for funding. He explains how this dilemma in public sector for opening data hinders the ability of private sector for initiating the project:   

\begin{quote}

\textit{``So when you formulate a project and makes through to the different stakeholders and the different gatekeepers, if you come out with that crazy idea, if you at top have people sitting that are not used to using smartphones, that may not be tuned into these things, or if you somewhere along the system have somebody saying: That?s great, but you know, if we are to innovative and we end up with a shit project that is going to cost us millions and we have nothing to show, then we are all getting fired. The minister is going to be upset, or the major is going to be upset.''} (Appendix \ref{appsec:hvidsteen}, 51:32)

\end{quote}

\noindent This indicates a need of \textit{innovation benefactors} \citep{CHESBROUGH1}, who focus on the early stage of the development and explores the value proposition of implementing such a system. This kind of primary research can incentivise and assure the investors (public sector) for funding open data initiatives.  \bigskip

\noindent The necessity of incorporating bottom-up approaches in an open data project has been already discussed. One way to take bottom-up approach is by involving citizens and other relevant actors in development process. Adrian Ulisse explains the necessity of the citizens perspectives to understand citizen needs and to incentivise them to involve in the development process. 

\begin{quote}

\textit{``One of the things that we are looking at is how to encourage citizens to use their sensor devices in their smart phone to collect data on behalf of the city - why would you do that? Share these data with government? It's costing some of my battery time. What are the benefits for me?  That issue has not been thought through. But to go back to the point I started with: if you can make solving problems that are personal to citizens important and integrate that into what you are doing, then you stand a much better chance.''} (Appendix \ref{appsec:adrian}, 21:53)

\end{quote}

\noindent Similarly, Søren Kvist explains the necessity of understanding citizens problem by saying, 

\begin{quote}

\textit{``If they are not provided with the right technology, people will not use it or they will use it in unintended way.''} (Appendix \ref{appsec:kvist}, 27:20)

\end{quote} 

\noindent Citizen engagement is also viewed as a major factor in developing successful smart city initiatives (\ref{subsec:smartcitieswheel}). Lasse Vestergaard argues that, 

\begin{quote}

\textit{``Conceptually, people should be able to participate in their own cities and do stuff more actively and I will say that open data can help quite a lot there.''} (Appendix \ref{appsec:lassesteenbockvesteraard}, 20:14)

\end{quote}

\noindent Søren Kvist explains the plans of Copenhagen Connecting to involve citizens. He says:

\begin{quote}

\textit{``to make sure that we don't roll out solutions that are not going to be a success, we are going to make collaborations with people that are experts. It could be citizens and other key stakeholders in the city [\ldots]. ''} (Appendix \ref{appsec:kvist}, 30:50)

\end{quote}

\noindent He further explains the goals of Copenhagen Solution Lab to support citizens:

\begin{quote}

\textit{``One of the main objectives of Copenhagen Solution Lab is to support citizens, so we don't build solutions that the citizens don't need [\ldots]. So this work that we are going to start up now is going to bring these different institutions together, for example the research institutions, in regards to make solutions that are viable that people can accept.''}
\end{quote}

\noindent The analysis of above statements clearly depicts the importance of involving citizens in open data projects but Adrian Ulisse also emphasizes that it is necessary to identify relevant actors in the particular project. He argues that sometimes it might not be necessary to involve citizens:

\begin{quote}

\textit{``Why wouldn't the private and public sector be collaborating together to solve a problem around the high street or parking or energy? You don't need citizen engagement for the obvious.''} (Appendix \ref{appsec:adrian}, 26:50)

\end{quote}

\noindent He also explains the reason for not involving citizens by saying, 

\begin{quote}

\textit{``One of the reasons why I say it's difficult is that citizens are generally lazy. The majority of us are lazy and we will expect things to happen for us and wonder why things don't happen for us. The engagement with the citizen peace is important - has to recognize that we are lazy. If we recognize that, then we are able to understand which engagements are actually useful.''} (Appendix \ref{appsec:adrian}, 26:50)

\end{quote}

\subsection{Maturity -- a collective open data mindset}

We want to briefly elaborate on the concept of maturity and hold the statements from the interviewees up against what we already know about maturity from the literature review, section \ref{sec:maturity}. This is a crucial elaboration because the concept of maturity is the pivot of our research and we need to find out how to grasp the concept in an open data context. \bigskip

\noindent While going through the nature of business silos breakdown in a smart city context in subsection \ref{subsec:silosbreakdown} we repeatedly referred to a special kind of understanding of the value of holistic thinking. For initiatives based directly on open data or open data as an enabler of other data-driven smart city initiatives to become successful and sustainable, the actors have to be willing to share their data and take in the data of others and by that break down their business silo. They have to acknowledge that a mutual learning process regarding open data can lead to two-sided, sustainable, and valuable outcome. This understanding is what we now refer to as maturity, just as in the introduction of our thesis, section \ref{sec:researchbackgound}. One difference is that we now have confirmed our initial assumption about open data mindset maturity in a smart city context. Another learning is that there are different perspectives on and levels of this maturity: (1) the individual maturity of a smart city actor, (2) the collective maturity of the specific subsystem/project, and (3) the collective maturity of the whole smart city, which can be considered as an unreachable thing to measure and treat because of its complexity. 

Furthermore there is a maturity factor regarding the understanding of data as such among the actors and finally there is the maturity or quality of the actual data to be opened. Even though our research is addressing the maturity of open data mindsets among smart city actors we are mentioning these factors because they seem like inevitable parts of mindset maturity. Increasing data maturity/quality is necessary for an open data mindset maturity to grow and vice versa. And the same applies to core data understanding. \bigskip

\noindent Our usage of grounded theory in our research has enabled us to sketch up a taxonomy for open data maturity categories in smart cities. This is shown in table \ref{tab:maturityperspectives}.

\begin{table}[H]
\centering

\begin{tabular}{|c|p{7cm}|} \hline
\textbf{Category 1} & The individual maturity of a smart city actor \\ \hline
\textbf{Category 2} & The collective maturity of the specific subsystem/project \\ \hline
\textbf{Category 3} & The collective maturity of the whole smart city \\ \hline
\textbf{Category 4} & Maturity towards understanding the core data among the actors \\ \hline
\textbf{Category 5} & The maturity or quality of the actual data to be opened \\ \hline

\end{tabular}
\caption{\textit{Maturity categories in an open data, smart city context}}
\label{tab:maturityperspectives}
\end{table}

\subsubsection{What our interviewees say about maturity}

We will highlight some quotes from the interviews that depict some of the maturity categories that we have identified. \bigskip



\noindent Adrian Ulisse addresses how maturity categories 2, 4, and 5 are interlinked:

\begin{quote}
\textit{``The reality is that the majority of the data is poor quality so it's very difficult to use. The understanding of what problem you are trying to solve is not being thought through. So as they may publish one data element you can't solve the problem without other elements of data and that might be from the private sector, it might as well be from citizens.'} (Appendix \ref{appsec:adrian}, 23:20)
\end{quote}

\noindent Kristoffer Hvidsteen also links that to maturity category 1:

\begin{quote}
\textit{``If you have good data capability and analytic capability you are able to understand the consumption much much better and meet those demands much more accurately. So opening up the data is one part of it but that just becomes a cloud of data. We need to be able to understand and contextualize it for it to have value.'')} (Appendix \ref{appsec:hvidsteen}, 16:10)
\end{quote}

\noindent Adrian goes on and links that to the maturity of the whole city and depicts that as a constraint for maturity development in smaller parts of the city:

\begin{quote}
\textit{``Certainly, a government that stays being in power for more than two terms often doesn't want to change what it set up in the first term. So it takes another government to come in and change some of the institutions that it doesn't agree with. There is certainly something around that, I don't know what the answer is, but you can just see a mismatch between these institutions and the ability to have everybody to work together collaboratively.''} \ref{appsec:adrian}, 37:23)
\end{quote}

\noindent So the maturity of the city, municipality, or whatever institution that set up de facto rules and realms for collaboration have a big role to play. Even though this is a much harder kind of maturity to address and process:

\begin{quote}
\textit{``I think one of the biggest challenges in all this is the institutional frameworks that we set up that stop collaboration unintentionally.''} (Appendix \ref{appsec:adrian}, 34:12)
\end{quote}

\noindent Søren Møller Jensen has a spot on statement explaining what individual maturity (category 1) consists of:

\begin{quote}
\textit{``\ldots you need to consider what would might incentives be for me to open up the access to that data for another company.''} (Appendix \ref{appsec:sorenmollerjensen}, 08:18)
\end{quote}

\noindent An actor can be considered mature if he is able to articulate direct incentives for him to open up data. This maturity is of course causal to the maturity of the other relevant actors in a subsystem and therefore categories 1 and 2 are causal.

Søren Møller Jensen goes on and explains that open data mindset maturity is about understanding how to exploit the synergies between sectors by means of data sharing. This requires category 2 maturity because several actors need to collaborate on this:

\begin{quote}
\textit{``you [have to] believe that you can actually gain something from trying to come up with new solutions even though you cannot formulate those new solutions in detail when you start out. I see the same with open data and the need to invent something. Sometimes if you have access to the data it's just a time effort to try to see what values lies within that data.''} (Appendix \ref{appsec:sorenmollerjensen}, 21:16)
\end{quote}

\noindent To be able to establish the required infrastructures for data collection and sharing the society also has to be mature to understand its justification. This is category 3 maturity which is dependent on category 4 maturity:

\begin{quote}
\textit{``It's not that difficult to figure out that if we build a highway what can we do with that. We can have cars and trucks and others driving on that. In that sense it's very easy. But when somebody suggests that we should use a truck loads of money on a wireless infrastructure [they think] why? Its not even visible. [A highway] is a physical construction. You can see it's there. We know what the money was spent on and we pay for it. I mean the society needs to be mature and that is society maturity when it comes to digitalizing products and services as well.''} \ref{appsec:sorenmollerjensen}, 01:03:12)
\end{quote}

\noindent Henrik Korsgaard also explains how an actor have to have the

\begin{quote}
\textit{``understanding that you might not be creating value that is directly returned to yourself but it is distributed along a very complex network of stakeholders.''} (Appendix \ref{appsec:henrik}, 14:36)
\end{quote}

\noindent He further depicts the necessity for category 4 maturity and how it is related to categories 1 and 2: 

\begin{quote}
\textit{``if we talk about fixing some of the issues then get municipal case workers and employees and policy-makers and a lot of people within the governance bodies to understand what data is. This will be the first step towards actually discussing some of the social sustainable issues. [\ldots] If you make decisions on it, you should be able to at least understand the landscape on a more detailed level that the current people do. And I think that would both ensure some sustainable growth but also a more sustainable business perspective as well.''} (Appendix \ref{appsec:henrik}, 33:04-36:45)
\end{quote}

\noindent Søren Kvist is elaboration on the role of data created by the public sector as a basis for open innovation. It has to be real-time data which is relevant and well-structured. This is indeed category 5 maturity:

\begin{quote}
\textit{``one of the main obstacles is that the data that we have and provide for students and companies is simply not enough. It is not enough just to open up our system data from the city, we have to provide real-time data, because it especially when we provide real-time data that you can actually make solutions that are interesting for business and entrepreneurs to build data-driven solutions on.''} (Appendix \ref{appsec:kvist}, 32:16)
\end{quote}

\noindent Lasse Vestergaard is also discussing this issue of category 5 maturity and he concretely explains the interdependencies between the quality of the data and the open data mindset maturity of the actors:

\begin{quote}
\textit{``to up the value or the quality of the data, that means having real time data and have it in structured format so that you can use the data directly within your apps because you have this API access so there is computational access to data or automatic access to data. So that is happening but that is going really slow and that is the first thing.''} (Appendix \ref{appsec:lassesteenbockvesteraard}, 12:21)
\end{quote}

\begin{quote}
\textit{``So, if the quality of the data is not good enough you cannot create anything but if you don't understand the data it's really hard too because I guess you need to work from both sides: You need to have a better quality of data but you need to also get a better mindset for the better understanding of what you can do with the data.''} (Appendix \ref{appsec:lassesteenbockvesteraard}, 40:18)
\end{quote}

\noindent He further depicts that the ideal smart city should think and behave as an organism -- one can interpret that as the smart city should strive for working as an organisation. This is not possible from a complex city perspective but can be possible in a subsystem level:

\begin{quote}
\textit{``sustainability also comes in to the area of `OK, How can we jointly do stuff and how can we be more like an organism?' So the city should be like an organism. That means everyone should essentially be able to help everyone.''} (Appendix \ref{appsec:lassesteenbockvesteraard}, 21:15)
\end{quote}

\newpage

\subsection{Summarizing the findings}


\noindent Summarizing the findings of three topics that were the result of selective coding (section \ref{sec:findings}), we can claim that sustainable development of smart cities requires the city actors to break down the silos, develop cross-sectoral thinking and  become more agile and collaborate in new ways. Institutional design is pivotal in breaking down of silos and hence, ripping the value from the synergies between different cross-sector. Open data is a way of creating integration across silos and by that developing a sustainable collaborative environment for sustainable development of smart cities. This requires the smart city actors to open their data across sector boundaries. Despite understanding the value of cross sectoral open data, unaligned mindsets of the actors and  quality of data are seen as big obstacles in opening and sharing of data. So, maintaining the quality of data and developing the mindset that understands the value of data and its exposure mechanisms are the major factors for silo breakdown. Furthermore, it has been identified to be unrealistic to realize the optimal value from whole open data paradigm at once. So, concrete projects with clear short-term goals should be formulated, which can grow gradually as the open innovation grows and a whole ecosystem emerge.  \bigskip

\noindent As a complex ecosystem, it is very challenging or almost impossible to optimize a city taking a system-wide top-down approach. Instead it can be started from a subsystems (systems perspectives) level and further extended to bigger systems level striving for whole city level. This we argued as a bottom-up system optimization. Looking into which approach to follow for open data system development, our findings depicts that a clear balance between a top-down approach and bottom-up approaches is needed. The development and deployment of open data initiatives/systems can be accomplished using top-down approach whereas further development and extension of system can be handled using bottom-up approach as it allows the participation of the citizens and other system actors, which eventually fosters open innovation. We have found that relevant actors for a particular project have to be identified. \bigskip

\noindent At last, by analysing the primary and secondary data thoroughly we identified that there are different perspectives on maturity and it has to be considered on different levels (such as individual level, system level, city level) of smart city development. Based on this, we categorised maturity in to five categories (table \ref{tab:maturityperspectives}). We also analysed how these maturity categories are interdependent. And finally we deduced that increasing all these maturity categories will lead to increase in the collective open data mindset maturity, which is an inevitable factor for developing smart cities holistically by means of open data. \bigskip